{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas计算（常用内建函数）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1、 pct_change()\n",
    "计算百分比变化Percentage Change"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "stock1 = pd.read_excel('sz50.xlsx',sheetname='600036.XSHG', index_col='datetime')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "one_day_change = stock1.close.pct_change()\n",
    "five_day_change = stock1.close.pct_change(5)\n",
    "ten_day_change = stock1.close.pct_change(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SRztcibRHAVNERESOs/ngZh7+5GGuHHclF4y6oNP2LduWaJhs17X0YKbF+Yf5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\nlvX5s0LJ4/X3QCZHpVJZ10gKVZ0Oj20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U0OnxJoFZVqNDiQFlfYXZEUyACY39MK3RriTS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Ko8tg5XK2N8HUxb5YeZWVTJ+hOpzO3vird951ox6JK67MO+F8awfLwPf0RnMu6DQ11fNiuTwYjn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\n4wci5utle0UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x134f0872160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(figsize=(15,7))\n",
    "plt.plot(one_day_change.iloc[-50:], label='one')\n",
    "plt.plot(five_day_change.iloc[-50:], label='five')\n",
    "plt.plot(ten_day_change.iloc[-50:], label='ten')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2、 cov() & cor()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$cov = E[(x - \\mu x)(y-\\mu y)]$\n",
    "\n",
    "$cor = cov/ (\\sigma x* \\sigma y)$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# example:\n",
    "import numpy as np\n",
    "\n",
    "aArray = np.array([4,1,3,3,4,5])\n",
    "bArray = np.array([2,2,2,1,2,3])\n",
    "\n",
    "cov = ((aArray-aArray.mean())*(bArray-bArray.mean())).sum()/(len(aArray)-1)\n",
    "cov1 = ((aArray-aArray.mean())*(bArray-bArray.mean())).sum()/len(aArray)\n",
    "cor = cov1/(aArray.std()*bArray.std())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.4"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.4"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.cov(aArray,bArray)[0][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.4629100498862757"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.46291004988627565"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.corrcoef(aArray,bArray)[0][1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**cov()**\n",
    "\n",
    "计算协方差Covariance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "stock2 = pd.read_excel('sz50.xlsx',sheetname='600050.XSHG', index_col='datetime')\n",
    "stock3 = pd.read_excel('sz50.xlsx',sheetname='601318.XSHG', index_col='datetime')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "five_day_df = pd.concat([stock1.close.pct_change(5),stock2.close.pct_change(5),stock3.close.pct_change(5)],keys=['stock1','stock2','stock3'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                       stock1    stock2    stock3\n",
      "datetime                                         \n",
      "2017-11-14 15:00:00  0.036622 -0.014538  0.077249\n",
      "2017-11-15 15:00:00  0.029140  0.018947  0.071039\n",
      "2017-11-16 15:00:00  0.038049 -0.029293  0.100700\n",
      "2017-11-17 15:00:00  0.085355 -0.034102  0.076982\n",
      "2017-11-20 15:00:00  0.103342 -0.016064  0.079239\n"
     ]
    }
   ],
   "source": [
    "print(five_day_df.tail())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          stock1    stock2    stock3\n",
      "stock1  0.001271  0.000139  0.000806\n",
      "stock2  0.000139  0.003739  0.000608\n",
      "stock3  0.000806  0.000608  0.001203\n"
     ]
    }
   ],
   "source": [
    "print(five_day_df.cov())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**corr()**\n",
    "\n",
    "计算相关系数Correlation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          stock1    stock2    stock3\n",
      "stock1  1.000000  0.085415  0.652129\n",
      "stock2  0.085415  1.000000  0.315773\n",
      "stock3  0.652129  0.315773  1.000000\n"
     ]
    }
   ],
   "source": [
    "# 相关系数\n",
    "correlation = five_day_df.corr()\n",
    "print(correlation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          stock1    stock2    stock3\n",
      "stock1  1.000000 -0.003432  0.659493\n",
      "stock2 -0.003432  1.000000  0.165067\n",
      "stock3  0.659493  0.165067  1.000000\n"
     ]
    }
   ],
   "source": [
    "# spearman排序相关性\n",
    "spearman = five_day_df.corr(method='spearman')\n",
    "print(spearman)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3、 rank()\n",
    "数据排序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                       stock1    stock2    stock3\n",
      "datetime                                         \n",
      "2017-11-14 15:00:00  0.036622 -0.014538  0.077249\n",
      "2017-11-15 15:00:00  0.029140  0.018947  0.071039\n",
      "2017-11-16 15:00:00  0.038049 -0.029293  0.100700\n",
      "2017-11-17 15:00:00  0.085355 -0.034102  0.076982\n",
      "2017-11-20 15:00:00  0.103342 -0.016064  0.079239\n"
     ]
    }
   ],
   "source": [
    "print(five_day_df.tail())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     stock1  stock2  stock3\n",
      "datetime                                   \n",
      "2017-11-14 15:00:00     2.0     4.0     3.0\n",
      "2017-11-15 15:00:00     1.0     5.0     1.0\n",
      "2017-11-16 15:00:00     3.0     2.0     5.0\n",
      "2017-11-17 15:00:00     4.0     1.0     2.0\n",
      "2017-11-20 15:00:00     5.0     3.0     4.0\n"
     ]
    }
   ],
   "source": [
    "# 正向纵序\n",
    "print(five_day_df.tail().rank(axis=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     stock1  stock2  stock3\n",
      "datetime                                   \n",
      "2017-11-14 15:00:00     2.0     3.0     1.0\n",
      "2017-11-15 15:00:00     2.0     3.0     1.0\n",
      "2017-11-16 15:00:00     2.0     3.0     1.0\n",
      "2017-11-17 15:00:00     1.0     3.0     2.0\n",
      "2017-11-20 15:00:00     1.0     3.0     2.0\n"
     ]
    }
   ],
   "source": [
    "#横向倒序\n",
    "print(five_day_df.rank(axis=1, ascending=False).tail())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4、 rolling()\n",
    "滚动计算"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "rolling = stock1.close.rolling(window=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "datetime\n",
      "2017-11-14 15:00:00    108.1320\n",
      "2017-11-15 15:00:00    108.2855\n",
      "2017-11-16 15:00:00    108.4850\n",
      "2017-11-17 15:00:00    109.0060\n",
      "2017-11-20 15:00:00    109.8100\n",
      "Name: close, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(rolling.mean().tail())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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bPUnfPQLLnoSaSvANaP3eonTzOUlTwFENG940+5xCYjs/fumcTe/C/JvNz6XebcshNrXj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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x134f5fdc358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,7))\n",
    "plt.plot(rolling.mean())\n",
    "plt.plot(stock1.close)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5、 expanding\n",
    "expanding不会返回NaN，功能与rolling相似。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sn = pd.Series([1, 2, np.nan, 3, np.nan, 4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "print(sn.expanding().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "print(sn.cumsum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "print(sn.cumsum().fillna(method='ffill'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6、 apply() & aggregate()\n",
    "\n",
    "**apply**\n",
    "\n",
    "调用自定义函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     close   high    low   open      volume\n",
      "datetime                                                   \n",
      "2017-11-14 15:00:00   5.63   5.63   5.70   4.83  45715400.0\n",
      "2017-11-15 15:00:00   5.63   5.63   5.70   5.55  45715400.0\n",
      "2017-11-16 15:00:00   5.95   5.63   5.70   5.55  45599200.0\n",
      "2017-11-17 15:00:00  11.06  10.17   8.06   6.83  55576000.0\n",
      "2017-11-20 15:00:00  13.96  13.92  10.34  10.82  55576000.0\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "def cal_range(array):\n",
    "    return array.max() - array.min()\n",
    "\n",
    "print(stock1.rolling(10).apply(cal_range).tail())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**aggregate**\n",
    "\n",
    "聚合，主要用于处理数据运算(诸如统计平均值,求和等)，并返回计算后的运算结果。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                       stock1    stock2    stock3\n",
      "datetime                                         \n",
      "2017-11-14 15:00:00  0.025171  0.478886  0.434446\n",
      "2017-11-15 15:00:00  0.050571  0.396198  0.438228\n",
      "2017-11-16 15:00:00  0.071251  0.293819  0.494201\n",
      "2017-11-17 15:00:00  0.193616  0.243951  0.563012\n",
      "2017-11-20 15:00:00  0.339433  0.238697  0.643087\n"
     ]
    }
   ],
   "source": [
    "# 对多只股票进行求和\n",
    "import numpy as np\n",
    "sum_agg = five_day_df.rolling(10).aggregate(np.sum)\n",
    "print(sum_agg.tail())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                          sum      mean       std\n",
      "datetime                                         \n",
      "2017-11-14 15:00:00  0.025171  0.002517  0.026701\n",
      "2017-11-15 15:00:00  0.050571  0.005057  0.028006\n",
      "2017-11-16 15:00:00  0.071251  0.007125  0.029727\n",
      "2017-11-17 15:00:00  0.193616  0.019362  0.034364\n",
      "2017-11-20 15:00:00  0.339433  0.033943  0.036102\n"
     ]
    }
   ],
   "source": [
    "# 对stock1进行多个不同的计算\n",
    "multi_agg = five_day_df.stock1.rolling(10).agg([np.sum, np.mean, np.std])\n",
    "print(multi_agg.tail())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                       stock1    stock2    stock3\n",
      "datetime                                         \n",
      "2017-11-14 15:00:00  0.171306  0.049099  0.046782\n",
      "2017-11-15 15:00:00  0.159352  0.048760  0.047016\n",
      "2017-11-16 15:00:00  0.169747  0.046769  0.049882\n",
      "2017-11-17 15:00:00  0.233389  0.046673  0.052029\n",
      "2017-11-20 15:00:00  0.350535  0.046850  0.053621\n"
     ]
    }
   ],
   "source": [
    "# 针对不要数据用不同算法\n",
    "multi_algo = five_day_df.rolling(20).agg({'stock1' : np.sum,\n",
    "       'stock2' : np.std,\n",
    "       'stock3' : np.mean})\n",
    "\n",
    "print(multi_algo.tail())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              high     low   close    open\n",
      "datetime                                  \n",
      "2017-10-29  112.29  105.38  112.13  106.66\n",
      "2017-11-05  111.93  106.22  107.98  111.05\n",
      "2017-11-12  109.49  104.87  108.02  107.34\n",
      "2017-11-19  117.67  108.46  117.24  108.46\n",
      "2017-11-26  122.50  116.20  121.82  116.92\n"
     ]
    }
   ],
   "source": [
    "# resample成周线后用agg获取所需要的数据\n",
    "print(stock1.resample('W').agg({'high':'max','low':'min', 'close':'last', 'open':'first'}).tail())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Computing rolling pairwise covariances and correlations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                              stock1    stock2    stock3\n",
      "datetime                                                \n",
      "2017-11-17 15:00:00 stock1  0.000743  0.000248  0.000773\n",
      "                    stock2  0.000248  0.001945  0.000923\n",
      "                    stock3  0.000773  0.000923  0.001420\n",
      "2017-11-20 15:00:00 stock1  0.000931  0.000207  0.000865\n",
      "                    stock2  0.000207  0.001925  0.000875\n",
      "                    stock3  0.000865  0.000875  0.001438\n"
     ]
    }
   ],
   "source": [
    "## 50天滚动的五日收益协方差\n",
    "\n",
    "cov_50 = five_day_df.rolling(50).cov()\n",
    "\n",
    "print(cov_50.tail(6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                              stock1    stock2    stock3\n",
      "datetime                                                \n",
      "2017-11-17 15:00:00 stock1  1.000000  0.206307  0.752711\n",
      "                    stock2  0.206307  1.000000  0.555120\n",
      "                    stock3  0.752711  0.555120  1.000000\n",
      "2017-11-20 15:00:00 stock1  1.000000  0.154276  0.747151\n",
      "                    stock2  0.154276  1.000000  0.525728\n",
      "                    stock3  0.747151  0.525728  1.000000\n"
     ]
    }
   ],
   "source": [
    "## 50天滚动的五日收益相关性\n",
    "\n",
    "corr_50 = five_day_df.rolling(50,).corr()\n",
    "print(corr_50.tail(6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rw/3vHsA3Ht+AS+dlY1NtF6ZnJeCSOdkhvT6FlkET+Dbd7+YPZSKisWrqHkCf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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x134f367a8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,7))\n",
    "plt.plot(corr_50.unstack()['stock1','stock3'])\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
